Abstract Making agriculture sustainable is a global challenge. In the European Union (EU), the Common Agricultural Policy (CAP) is failing with respect to biodiversity, climate, soil, land degradation as well as socio-economic challenges. The European Commission's proposal for a CAP post-2020 provides a scope for enhanced sustainability. However, it also allows Member States to choose low-ambition implementation pathways. It therefore remains essential to address citizens' demands for sustainable agriculture and rectify systemic weaknesses in the CAP, using the full breadth of available scientific evidence and knowledge. Concerned about current attempts to dilute the environmental ambition of the future CAP, and the lack of concrete proposals for improving the CAP in the draft of the European Green Deal, we call on the European Parliament, Council and Commission to adopt 10 urgent action points for delivering sustainable food production, biodiversity conservation and climate mitigation. Knowledge is available to help moving towards evidence-based, sustainable European agriculture that can benefit people, nature and their joint futures. The statements made in this article have the broad support of the scientific community, as expressed by above 3,600 signatories to the preprint version of this manuscript. The list can be found here (https://doi.org/10.5281/zenodo.3685632). A free Plain Language Summary can be found within the Supporting Information of this article.

A roundtable discussion held at the fourth International Symposium on the Environmental Dimension of Antibiotic Resistance (EDAR4) considered key issues concerning the impact on the environment of antibiotic use in agriculture and aquaculture, and emissions from antibiotic manufacturing. The critical control points for reducing emissions of antibiotics from agriculture are antibiotic stewardship and the pre-treatment of manure and sludge to abate antibiotic-resistant bacteria. Antibiotics are sometimes added to fish and shellfish production sites via the feed, representing a direct route of contamination of the aquatic environment. Vaccination reduces the need for antibiotic use in high value (e.g. salmon) production systems. Consumer and regulatory pressure will over time contribute to reducing the emission of very high concentrations of antibiotics from manufacturing. Research priorities include the development of technologies, practices and incentives that will allow effective reduction in antibiotic use, together with evidence-based standards for antibiotic residues in effluents. All relevant stakeholders need to be aware of the threat of antimicrobial resistance and apply best practice in agriculture, aquaculture and pharmaceutical manufacturing in order to mitigate antibiotic resistance development. Research and policy development on antimicrobial resistance mitigation must be cognizant of the varied challenges facing high and low income countries.

Agricultural gaseous nitrogen emissions are mostly related to manure management, grazing and fertilisation. These emissions include ammonia (NH3), nitrous oxide (N2O), nitric oxide (NO) and di-nitrogen (N2). Most of the non-methane volatile organic compounds (NMVOC) emissions originate from livestock farming, but also from cultivated crops. All these emissions are inventoried and reported for the UN Convention on Long-range Transboundary Air Pollution (CLRTAP), EU National Emission Ceilings Directive (2001/81/EC) and the UN Framework on Climate Change (UNFCC). In Finland, a specific national model for gaseous nitrogen emissions from agriculture has been used for the inventory since 1998. The revised calculation model documented here is tied to the Finnish Normative Manure System, which provides data on manure quality and quantity for various livestock categories. The emission calculation follows the flow of total ammoniacal nitrogen (TAN) and total nitrogen (N) through the manure management systems, starting from excretion and ending at manure spreading. The main manure management phases considered in the calculation are livestock housing, manure storing and manure field application. The calculation also embeds estimations on emissions from grazing and outdoor yards, as well as emissions from the use of mineral fertilisers. The nitrogen calculation model provides data for the calculation of agricultural NMVOC emissions. All calculations are constructed in compliance with the Tier 2 method of the EMEP/EEA emission inventory guidebook (2016).

Mountain areas often hold special species communities, and they are high on the list of conservation concern. Global warming and changes in human land use, such as grazing pressure and afforestation, have been suggested to be major threats for biodiversity in the mountain areas, affecting species abundance and causing distribution shifts towards mountaintops. Population shifts towards poles and mountaintops have been documented in several areas, indicating that climate change is one of the key drivers of species' distribution changes. Despite the high conservation concern, relatively little is known about the population trends of species in mountain areas due to low accessibility and difficult working conditions. Thanks to the recent improvement of bird monitoring schemes around Europe, we can here report a first account of population trends of 44 bird species from four major European mountain regions: Fennoscandia, UK upland, south-western (Iberia) and south-central mountains (Alps), covering 12 countries. Overall, the mountain bird species declined significantly (-7%) during 2002-2014, which is similar to the declining rate in common birds in Europe during the same period. Mountain specialists showed a significant -10% decline in population numbers. The slope for mountain generalists was also negative, but not significantly so. The slopes of specialists and generalists did not differ from each other. Fennoscandian and Iberian populations were on average declining, while in United Kingdom and Alps, trends were nonsignificant. Temperature change or migratory behaviour was not significantly associated with regional population trends of species. Alpine habitats are highly vulnerable to climate change, and this is certainly one of the main drivers of mountain bird population trends. However, observed declines can also be partly linked with local land use practices. More efforts should be undertaken to identify the causes of decline and to increase conservation efforts for these populations.

Practising sustainable agriculture and forestry requires information on the state of forests and crops to support management. In precision agriculture, crops are observed in order to treat them precisely in the right place and at the right time, saving both production costs and the environment. Similarly, in forests, information on the composition and state of forest health are crucial to enable their sustainable management. In particular, climate-change-driven insect pests have increased, but economic and ecological losses can be reduced by the right actions if up-to-date and precise information on the health of forests is available. In recent years, drones with cameras have evolved into a flexible way to collect remote sensing data locally. Spectral cameras provide accurate information about the reflection properties of objects, and photogrammetric methods also provide a cost-effective way to collect three-dimensional (3D) data from an object. The objective of this work was to develop and assess drone-based 3D and spectral remote sensing techniques to classify the health status of individual trees and to estimate crop biomass, various biochemical parameters such as nitrogen content, and grass-feeding quality. The work developed a processing chain in which spectral and 3D features were extracted from remote sensing data. Then, combining the features with observations and reference measurements collected from plants, machine learning models were developed for tree health classification and estimation of crop-related parameters. The effects of different factors related to data collection and processing on classification and estimation accuracies were studied in order to generate knowledge on optimal sensors and methods. In general, radiometric corrections, spectral resolution, and the combined use of spectral and 3D features improved classification and estimation accuracies. However, the optimal sensors as well as the data collection and processing methods depend on the different applications and their accuracy requirements. This work was the first to demonstrate the ability of drone hyperspectral data to map the health status of a forest by classifying individual trees infested by bark beetles. The results of the work also showed that drone-based mapping offers a great tool to estimate agricultural crop parameters which can be applied to the optimization of various precision agriculture tasks. Kestävän maa- ja metsätalouden harjoittaminen vaatii tietoa metsien ja viljelykasvien tilasta päätöksenteon tueksi. Täsmämaataloudessa viljelykasveja havainnoidaan, jotta viljelytoimenpiteet voidaan kohdistaa oikeaan paikkaan ja oikea-aikaisesti säästäen sekä tuotantokustannuksia että ympäristöä. Metsissä tieto metsien terveydentilasta on tärkeää, jotta voidaan hillitä metsätuhojen leviämistä. Erityisesti hyönteistuhot ovat lisääntyneet voimakkaasti ilmastonmuutoksen vauhdittamana, mutta taloudellisia ja ekologisia tappiota voidaan vähentää oikeilla toimenpiteillä, jos on olemassa ajantasaisesta tietoa metsien terveydentilasta. Dronet ja niihin asennettavat kamerat ovat kehittyneet viime vuosina joustavaksi tavaksi kerätä kaukokartoitusaineistoa paikallisesti. Spektrikameroilla saadaan tarkkaa tietoa kohteen heijastusominaisuuksista, ja fotogrammetriset menetelmät mahdollistavat myös kustannustehokkaan tavan kerätä kohteesta kolmiulotteista (3D) tietoa. Tämän työn tavoitteena oli kehittää näihin aineistoihin nojautuen kaukokartoitusmenetelmiä yksittäisten puiden terveydentilan luokitteluun sekä viljelykasvien biomassan, erilaisten biokemiallisten parametrien, kuten typpipitoisuuden sekä nurmen ruokintalaadun, kuten D-arvon estimointiin. Työssä kehitettiin prosessointiketju, jossa kaukokartoitusaineistoista irrotettiin spektri- ja 3D-piirteitä, yhdistettiin ne kasveista kerättyihin havaintoihin ja mittauksiin sekä muodostettiin koneoppimismalleja puiden luokittelua ja viljelykasveihin liittyvien parametrien estimointia varten. Työssä verrattiin useiden aineistonkeräykseen ja -prosessointiin liittyvien tekijöiden vaikutuksia luokittelu- ja estimointitulosten tarkkuuteen optimaalisten menetelmien löytämiseksi. Esimerkiksi spektri- ja 3D-piirteiden hyödyntäminen yhdessä sekä radiometriset korjaukset paransivat yleisesti luokittelu- ja estimointitarkkuuksia. Optimaaliset sensorit sekä aineistonkeräys- ja käsittelytavat riippuvat kuitenkin eri sovelluksista ja niiden tarkkuusvaatimuksista. Työssä osoitettiin ensimmäistä kertaa dronesta kerätyn hyperspektrisen aineiston kyvykkyys metsän terveydentilan havainnoinnissa luokittelemalla kuuset kolmeen luokkaan kirjanpainajan aiheuttaman tuhon perusteella. Työn tulokset myös osoittivat drone-pohjaisen kartoituksen kyvyn estimoida erilaisia viljelykasvien parametreja, joita voidaan edelleen soveltaa suunniteltaessa esimerkiksi lisälannoitusta tai säilörehun optimaalista korjuuaikaa.

Agricultural diffuse pollution is a major environmental problem causing eutrophication of water bodies. Despite the problem is widely acknowledged, there has been relatively few major advances in mitigating the problem. We studied the effectiveness of biopolymer-based (tannin, starch, chitosan) natural coagulants/flocculants in treatment of two different agricultural wastewaters that differed in their level of phosphorus pollution and turbidity. We used jar-tests to test the effectiveness of the biopolymer coagulants in reducing water turbidity, total phosphorus, and total organic carbon (TOC) from the wastewaters. In more polluted water (total phosphorus: 300 µg/L, turbidity: 130 FNU, TOC: 30 mg/L), all tested biopolymers performed well. The best reductions for different biopolymer coagulants were 64–95%, 80–98% and 14–27%, for total phosphorus, turbidity and TOC, respectively. Tannin and chitosan coagulants performed the best at doses of 5–10 mL/L, whereas starch coagulants had the best performance at 1–2 mL/L doses. Tannin and chitosan coagulants performed clearly better than the starch coagulants. In less polluted water (total phosphorus: 74 µg/L, turbidity: 3.9 FNU, TOC: 21 mg/L), chitosan and starch coagulants did not produce flocs at any of the tested doses. Tannin coagulant performed the best at doses of 5–8 mL/L, where reductions were 70%, 82%, and 22%, for total phosphorus, turbidity and TOC, respectively. The great reductions of phosphorus and turbidity suggests that biopolymer coagulants could be applied in treatment of agricultural water pollution. The high phosphorus retention in the biodegradable biopolymer sludge suggests that the sludge can be readily used as a phosphorus fertilizer, which would aid the recycling of nutrients.

Environmental and political debate concerning the role of agriculture in sustainability has long been on the agenda. However, owing to climate change, an analysis of the transition to a low-carbon society must also be considered from the perspective of justice. Dairy farming, in particular, faces pressure in this context, when contemplating changing consumer behaviors and reduction in the carbon footprint of dairy products. Accordingly, many dairy farmers are struggling with the profitability and high production costs of farming. This study examines the experiences and perceptions of dairy farmers in Finland. The theoretical background is predicated upon the “just transition” literature. Additionally, recent literature regarding farmers' attitudes and agency, related to climate and environmental change, is utilized. A collaborative, empirical study of the Finnish dairy co-op Valio Ltd.‘s carbon-neutral milk chain program was conducted. The authors interviewed 18 dairy farmers and examined their motivations and barriers to carbon-neutral practices. Their experiences and perceptions of justice, in the context of a carbon-neutral milk chain, were studied. This study elucidates how to shift to carbon-neutral agriculture in such a way that dairy farmers perceive this systemic change as justified and acceptable. The results indicate that from the farmers' perspective, three key justice issues need consideration: 1) profitability of farming, 2) blaming of farmers, and 3) use of agricultural peatlands.

Megatrends (urbanization, digitalization, globalization, climate change, etc.) are mainstream developments that affect most economic activities. These megatrends have varying incidences and impacts on individual entrepreneurs and enterprises, also in farming sector. A farmer can either ignore or try to adapt to or benefit from megatrends. This reaction depends on many things: individuals' futures orientation, management practices, business strategy, sunk costs, the life cycle and type of business, for example. The study explores the association between eight common megatrends and business strategies among a sample of Finnish dairy producers. The analysis is based on survey data from the year 2019 (n = 135) collected among a major Finnish dairy industry co-operative's contract producers. The respondents evaluated the expected impact of the megatrends on their own business within the next 10 years with 5-point Likert-type scale (-2 horizontal ellipsis +2). K-means cluster analysis was utilized to uncover a few basic settings in the association between megatrends and farmers behaviours. After trying out several numbers of clusters, a distinctive three cluster solution was found. Additionally, cluster member profiles were framed with farmers' Likert -scale responses. The analysis indicates that dairy farmers differ in their observation of megatrends. The results confirm that some of the farmers more or less ignore the common megatrends, whereas some other farmers adapt to or benefit from the common megatrends. Supporting farmers' futures consciousness will strengthen their capacities of coping in the changing business environment.

In Finland, a recent ecological classification of surface waters showed that the rivers and coastal waters need attention to improve their ecological state. We combined eco-hydrological and empirical models to study chlorophyll-a concentration as an indicator of eutrophication in a small agricultural river. We used a modified story-and-simulation method to build three storylines for possible changes in future land use due to climate change and political change. The main objective in the first storyline is to stimulate economic activity but also to promote the sustainable and efficient use of resources. The second storyline is based on the high awareness but poor regulation of environmental protection, and the third is to survive as individual countries instead of being part of a unified Europe. We assumed trade of agricultural products to increase to countries outside Europe. We found that chlorophyll-a concentration in the river depended on total phosphorus concentration. In addition, there was a positive synergistic interaction between total phosphorus and water temperature. In future storylines, chlorophyll-a concentration increased due to land use and climate change. Climate change mainly had an indirect influence via increasing nutrient losses from intensified agriculture. We found that well-designed agri-environmental measures had the potential to decrease nutrient loading from fields, as long as the predicted increase in temperature remained under 2 °C. However, we were not able to achieve the nutrient reduction stated in current water protection targets. In addition, the ecological status of the river deteriorated. The influence of temperature on chlorophyll-a growth indicates that novel measures for shading rivers to decrease water temperature may be needed in the future.